databricks-medallion-architecture

The medallion architecture in Databricks is a layered data design pattern using Bronze, Silver, and Gold tiers to organize ingestion, transformation, and analytics. It leverages Delta Lake and Unity Catalog to manage data quality, lineage, and governance across workloads.

To design Bronze, Silver, and Gold layers in Delta Lake, map data sources to Bronze for raw ingestion, build Silver transformations for quality and conformance, and create Gold tables with pre-aggregations and consumable business metrics for BI analytics.

Yes, you can use Unity Catalog for RBAC governance in a Databricks medallion architecture. It provides clear ownership, data lineage tracking, and access control across the Bronze, Silver, and Gold layers to ensure auditable data platforms.

Handle batch and streaming ingestion with Delta Lake by applying practical design patterns for incremental processing. Use MERGE operations and auto-ingest features to update data continuously across Bronze and Silver layers for scalable real-time and batch workloads.

The best way to optimize costs in a Databricks medallion data architecture is applying lifecycle patterns for storage and compute management. Delta Lake and Unity Catalog patterns help manage incremental processing, data retention, and query efficiency to reduce overall platform costs.